Azmi Hassan

Modelling of palm oil production using fuzzy expert system

The production of crude palm oil and palm kernel is a complex problem due to the influence of processing variables and environmental factors. These processing variables influence the amount of crude palm oil and palm kernel losses during processing. Instead of mathematical model, fuzzy logic approach provides a simpler and easier mechanism to describe the relationships between the processing variables and the amount of crude palm oil and palm kernel losses. In this study, four fuzzy expert system models were developed for each palm oil processing station. An approximation of centre of gravity method for defuzzification is also proposed to enable the development of the model using Microsoft^(R)Excel. For comparison purpose, the models were also developed using MATLAB^(R). Results obtained from the Excel model are found to be very close to the results from MATLAB.

Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system

In this paper, a modified genetic algorithm named as dynamic characterized genetic algorithm (DCGA) is proposed. The new DCGA is then integrated into adaptive beam forming technique to reduce the power usage of adaptive antenna at WCDMA base station (node B) for serving instantaneous mobile needs. As contradict to conventional GA, DCGA is able to adapt itself in chromosome representation and number of crossover points in order to reduce unnecessary searching space and thus, increase convergence rate efficiently. Power usage at node B is used as fitness function to compare the performance of DCGA and GA. Simulation result has shown that DCGA converges faster and is superior in adaptive beam forming in the aspect of power usage at node B as compared to conventional GA.

WCDMA downlink capacity improvement by using smart antenna

Heterogeneous type of users in modern mobile communication expect network service provider providing high-speed data, multimedia and voice services. However, capacity has always been an issue to any generation of mobile communication technologies as it is always inversely proportionate to QoS (quality of service) in nature. Hence, in order to increase the system capacity without jeopardizing the QoS, smart antenna was proposed to increase the spectral efficiency of the wireless channel. Many research works have shown that the system capacity of modern mobile communication can be improved by employing smart antenna, A dynamic radio network simulator was developed in Visual C++reg to study and estimate the downlink capacity of a WCDMA system with smart antenna. Capacity system by using different smart antenna strategies was studied in this research. Simulation was done based on single micro cell environment with considering interference from the first tier. User mobility is taken into account to provide a combined evaluation of radio resource management (RRM). Capacity system expressed in downlink outage under various simulation scenarios was represented in this paper

Lean production in improving supply chain performance through hybrid model SCOR 11.0 - system dynamics

Supply Chain Operation Reference (SCOR) is a method to measure supply chain serving the business process framework, performance indicators and unique technologies to support communication and collaboration among supply chain partners. The objective of this paper is to measure Supply Chain Management performance by using SCOR version 11.0 for production typology of MTS-MTO in Indonesian Batik Industry. This research combines SCORs model and System Dynamics in order to predict the complex activities on batik industry. The hybrid SCOR-SD could identify the interaction among five attributes with the associated variables simultaneously. The results are obtained after the performance of lean production application is increased and the targets are achieved, even exceeding the target. For reliability attributes that associated with perfect order fulfilment started from 2015 to 2019 respectively are calculated as 80.06%, 103.53%, 105.58%, 93.76%, and 72.17%. Responsiveness attributes associated with the order fulfilment cycle time, respectively 122.45%, 149.10%, 159.26%, 131.53%, and 119.36%. Attributes associated with the total cost of service charge respectively 93.46%, 93.53%, 93.45%, 93.49, and 93.49%. Attributes associated with cash management assets to cash cycle time in a row were 160%, 153%, 146.3%, 150%, and 126.7%. The latter attribute is agility attributes associated with supply chain flexibility upside respectively 100%, 87.2%, 100%, 82%, and 82%.

Knowledge-Based Genetic Algorithm for Multidimensional Data Clustering

In this paper, a new approach of genetic algorithm called knowledge-based Genetic Algorithm (KBGA-Clustering) is proposed for multidimensional data clustering . Basically, this method adopts knowledge of what called as appropriate cluster centre for a fixed number of k-cluster. The chromosome which has inappropriate genes will be penalised with maximum value to prohibit it in the next generation. The experimental result is also provided for KBGA-Clustering and Genetic Algorithm-Clustering (GA-Clustering) to present the performance. Based on the observation, KBGA-Clustering presents better performance and more optimum solution compared to conventional GA-Clustering.

The application of hybrid artificial intelligence techniques in the optimisation of crude palm oil production

The production of crude palm oil and palm kernel are greatly influenced by factors such as deterioration of the raw material, processing inefficiency as well as environmental condition. An optimisation model for the palm oil production is therefore critical in ensuring maximum revenue in production whilst minimising palm oil and palm kernel losses and production cost. The proposed optimisation model is an integration between fuzzy expert system and multi objective programming model. Four fuzzy expert models were developed for each processing station with the aim of achieving four objectives, ie. to maximise revenue, minimise total production costs as well as minimise the total amount of palm oil and palm kernel losses. Two heuristic optimisation methods, ie. Genetic Algorithm (GA) and Direct Random Search are applied to solve this problem. The model is able to optimise the revenue, production cost as well as the total amount of palm oil and palm kernel losses. The study has also shown that Genetic Algorithm results in more optimum solutions compared to the Direct Random Search method.

Downlink capacity improvement of WCDMA system by using adaptive antenna with novel MDPC beamforming technique

Smart antenna is a well known method to increase the spectral efficiency of the wireless channel and subsequently increase the mobile communication system capacity without jeopardizing the system QoS (De Sousa et al, 2003; Marikar, 2002). There are two major types of smart antenna systems; switch beam antenna and adaptive beam antenna. Adaptive antenna which has dynamic beam to cater for users needs is better in improving the system capacity but requires more advance beam forming algorithm and requires intensive processing power for beam forming. Thus, adaptive beamforming technique is critically important. In this paper, a novel adaptive downlink beam forming technique for WCDMA system namely Minimum Downlink Power Consumption (MDPC) is introduced. A dynamic radio network simulator was developed in Visual C++/spl reg/ to study the power consumption at WCDMA base station (Node B) and to estimate the downlink capacity improvement by implementing this novel algorithm. Simulation was done based on a single micro cell environment with consideration of interference from the first tier. User mobility is taken into account to provide a combined evaluation of Radio Resource Management (RRM). Capacity system expressed in downlink outage under various simulation scenarios was represented in this paper.

Performance evaluation of multi-user detection in CDMA using micro-genetic algorithm

Two main problems of multi-user communication systems are the multiple access interference (MAI) and the near-far effects. While the near-far effect problem can be approached by applying power control, the MAI problem requires individual receivers to identify the desired signal from interferences thus making multi-user detector a popular area of research. Genetic algorithms (GA) is a search and optimization technique that works by estimating multiple solutions in order to come with the best estimated solution. GA works iteratively over a population of solutions using crossover and mutation to simulate a potential solution. In this paper we examine the performance of a micro-genetic algorithm-based multi-user detector. Our simulation shows that /spl mu/GA achieves a performance close to an optimal detector.

Teletraffic performance of mobile cellular channel assignment using genetic algorithm

Teletraffic performance of channel assignment strategy with and without genetic algorithm (GA) integration is presented in this paper. Genetic algorithm (GA) D. Goldberg (1989) J.H. Holland (1975) which is a well-known method in solving various types of complex mathematical is integrated into ordinary channel assignment strategies to design a conflict-free channel assignment strategy that satisfies both the electromagnetic compatibility (EMC) constraints and traffic demand requirements W.K. Lai et al. (1996). The teletraffic performance is based on grade of service (GoS) of mobile cellular-system that can be predicted using Erlang-B and through simulation. Good agreement is obtained between the predicted results and simulation data. The simulation results show that GA has improved the GoS (grade of service) of cellular radio system in the aspect of blocking probability and C/I (carrier-to-interference ratio) median in mobile cellular system.